Noise Analysis Approach Research Articles

Modelling and simulation of electroencephalography instrumentation to study the epileptic seizure: a noise analysis approach

Modelling and simulation of electroencephalography instrumentation to study the epileptic seizure: a noise analysis approach

Modeling and simulation of electroencephalography (EEG) instrumentation to study the epileptic seizure: A noise analysis approach

Modeling and simulation of electroencephalography (EEG) instrumentation to study the epileptic seizure: A noise analysis approach

Improved DBSCAN Spindle Bearing Condition Monitoring Method Based on Kurtosis and Sample Entropy

An improved density-based spatial clustering of applications with noise (IDBSCAN) analysis approach based on kurtosis and sample entropy (SE) is presented for the identification of operational state in order to provide accurate monitoring of spindle operation condition. This is because of the low strength of the shock signal created by bearing of precision spindle of misalignment or imbalanced load, and the difficulties in extracting shock features. Wavelet noise reduction begins by dividing the recorded vibration data into equal lengths. Features like kurtosis and entropy in the frequency domain are used to generate feature vectors that indicate the bearing operation state. IDBSCAN cluster analysis is then utilized to establish the ideal neighborhood radius (Eps) and the minimum number of objects contained within the neighborhood radius (MinPts) of the vector set, which are combined to identify the bearing operating condition features. Finally, utilizing data from the University of Cincinnati, the approach was validated and assessed, attaining a condition detection accuracy of 99.2%. As a follow-up, the spindle’s vibration characteristics were studied utilizing an unbalanced bearing’s load bench. Bearing state recognition accuracy was 98.4%, 98.4%, and 96.7%, respectively, under mild, medium, and overload circumstances, according to the results of the experimental investigation. Moreover, it shows that conditions of bearings under various unbalanced loads can be precisely monitored using the proposed method without picking up on specific sorts of failures.

Frequency-domain analysis of dual-loop optoelectronic oscillators.

Optoelectronic oscillators (OEOs) are hybrid systems consisting of optical and radio-frequency (RF) parts that are used to produce ultralow phase noise RF oscillations. Dual-loop OEOs can overcome some problems incorporated with single-loop OEOs such as the mode-hopping phenomenon and the large spurious peaks in the phase noise. Therefore, they are usually considered the practical implementation of many OEOs. Here, a frequency-domain steady-state and phase noise analysis approach of these systems is presented, based on the conversion matrix approach. Compared with the existing time-domain analysis approaches, it requires much smaller run times. Compared with the other frequency-domain modeling approaches, such as the linear-time-invariant phase transmission models, it can take all noise-transferring phenomena between various sidebands and all amplitude-noise to phase-noise conversions and vice versa into account. Therefore, it can be regarded as a comprehensive analysis approach to dual-loop OEOs. The validity of the new approach is verified by comparing its results with those of the previously published formulations in the literature.

Frequency‐domain behavioural noise analysis of analogue phase‐locked loops

A frequency-domain approach for phase noise analysis of integer-N multiplier-type phase-locked loops (PLLs), based on the conversion matrix approach, is introduced that can take all non-linearities in the loop into account. It can also characterise all kinds of power spectral densities and correlation between variables and all aspects of phase noise-to-phase noise or amplitude noise-to-phase noise (AN–PN) conversions. The noise transfer between various sidebands is also taken into account. This is especially important for characterising the folding of the voltage-controlled oscillator's phase noise which results in the phase noise augmentation at small frequency offsets. Unlike the linear phase-domain models, the stochastic phase noise local maxima at large offset frequencies are also accurately characterised. Giving the phase/amplitude noise spectra of various PLL blocks, this approach computes the resulting output phase noise spectrum. The validity of the new approach is verified by comparing its results with those of a numerical time-domain stochastic simulation. The proposed method has far much faster runtimes, independent of the time constants in the system, compared to the corresponding time-domain methods that allow a convenient simulation-based design of PLLs especially at radio frequencies.

Weighted Local Times of a Sub-fractional Brownian Motion as Hida Distributions

The sub-fractional Brownian motion is a Gaussian extension of the Brownian motion. It has the properties of self-similarity, continuity of the sample paths, and short-range dependence, among others. The increments of sub-fractional Brownian motion is neither independent nor stationary. In this paper we study the sub-fractional Brownian motion using a white noise analysis approach. We recall the represention of sub-fractional Brownian motion on the white noise probability space and show that Donsker's delta functional of a sub-fractional Brownian motion is a Hida distribution. As a main result, we prove the existence of the weighted local times of a $d$-dimensional sub-fractional Brownian motion as Hida distributions.

On denoising satellite altimeter measurements for high-resolution geophysical signal analysis

Abstract Satellite radar altimeter observations are key to advanced studies in ocean dynamics, particularly those focusing on mesoscale processes. To resolve scales below about 100 km, because altimeter measurements are often characterized by a low signal-to-noise ratio (SNR), low-pass filtering or least-squares curve fitting is generally applied to smooth the data before analysis. Here, we present an alternative method. It is based on Empirical Mode Decomposition (EMD) developed to analyze non-stationary and non-linear processes, which adaptively projects a signal on a basis of empirical AM/FM functions called Intrinsic Modulation Functions (IMFs). Applied to a Gaussian noise signal, the EMD provides a set of IMFs with a predictable distribution of noise energy that can be exploited by wavelet-inspired threshold methods to provide an efficient approach to data denoising. The EMD method performs a local analysis of the SNR, does not require a priori assumptions about the underlying geophysical signal, e.g., its degree of smoothness or its compliance with a particular mathematical framework. The signal is simply assumed to be the sum of a piecewise-smooth deterministic part and a stochastic part. The proposed EMD-based denoising approach is therefore well suited for mapping non-linear features, such as strong gradients, and extreme values without significant smoothing. Using Jason-2, Cryosat-2, and Saral/AltiKa significant wave height measurements, the method provides an effective means of mapping overlooked geophysical variability of sea state at scales between about 100 km and 25 km, a range largely impacted by low SNR. Below 25 km, a spectral hump caused by inhomogeneities in the altimeter footprint essentially dominates the signal. In addition, the EMD method provides a consistent approach for long-term noise analysis and monitoring under global and local conditions. The proposed method is a step forward that will enable better exploitation of the unique set of altimeter observations that now covers more than 25 years.

Weighted Local Times of a Sub-fractional Brownian Motion as Hida Distributions

The sub-fractional Brownian motion is a Gaussian extension of the Brownian motion. It has the properties of self-similarity, continuity of the sample paths, and short-range dependence, among others. The increments of sub-fractional Brownian motion is neither independent nor stationary. In this paper we study the sub-fractional Brownian motion using a white noise analysis approach. We recall the represention of sub-fractional Brownian motion on the white noise probability space and show that Donsker's delta functional of a sub-fractional Brownian motion is a Hida distribution. As a main result, we prove the existence of the weighted local times of a $d$-dimensional sub-fractional Brownian motion as Hida distributions.

Computer‐aided noise analysis of a multiwall carbon nanotube

In this work, a novel approach for the computer-aided noise analysis of a multiwall carbon nanotube (MWCNT) is proposed. A transmission line model of the MWCNT and a noise correlation matrix based on admittance representation are used for the computer-aided noise analysis. This work presents a simple, fast and effective noise analysis approach for the MWCNT. The noise figure is computed for different values of the parameters of the MWCNT for determining the effects of parameter values on the noise figure of the MWCNT. The results of the computer-aided noise analysis of the MWCNT are given and discussed in detail. According to the results, the variation of the distance from the ground plane of the outer shell has little effect on the value of noise figure, when the value of inner radius or the total number of shells increases the value of noise figure decreases. Therefore the noise figure decreases with increasing diameter because the diameter increases with the increasing value of inner radius and the total number of shells. The value of noise figure increases when the value of nanotube length or physical absolute temperature increases. The value of noise figure decreases with the decreasing value of source admittance.

Hybrid Acoustic Noise Analysis Approach of Conventional and Mutually Coupled Switched Reluctance Motors

This paper presents a method to calculate the acoustic noise of conventional switched reluctance motor (CSRM) and mutually coupled switched reluctance motor (MCSRM). This method is based on dynamic electromagnetic models, combined with analytical estimation of the stator eigenmodes and radiation efficiency, considering the switching effects and frame effects. The proposed method is applied to predict and compare the acoustic noise performances of a CSRM and an MCSRM in a wide speed range. The results are validated using commercial finite element analysis software, JMAG for electromagnetics and ACTRAN for acoustics. An acceleration test based on a setup with a 12/8 CSRM is used for experimental validation. Results show that the proposed method can provide reliable prediction of main acoustic noises during acceleration.

Experimental Setup and Methodology to Carryout Fatigue Testing of Spiral Bevel Gears Used in Differential Gear Box Using NVH Approach

Currently the fatigue testing of bevel gears are being done by using non rotating type of fixtures that applies fatigue load on a single tooth, which does not resemble the actual loading condition in an automotive differential gear box. This paper discusses the experimental setup with the noise and vibration analysis approach to determine the signature of failures of spiral bevel gears. The proposed experimental setup seems promising for further research and development in the fatigue testing of spiral bevel gears. The Crown pinion and wheel assembly is used for the testing. The pinion is connected to the electric 3 phase AC motor of 75HP with a suitable coupling and the crown wheel is mounted on the half axle shaft, which in turn is connected to an electric dynamometer. The speed/torque of electric motor and the load applied by the dynamometer can be varied. The acoustic sensor is mounted near the differential gear box and the accelerometers are mounted on the Pinion bearing, Crown wheel bearing and the half axle bearing. A four channel data acquisition system is used to log data in time domain (raw data) by three accelerometers and an acoustic sensor. The variations of sound pressure(dB) v/s time, sound Pressure(FFT-(RMS)) amplitude v/s Frequency, Acceleration v/s Time, Octave analysis i.e., Band power v/s Frequency, Noise spectrum Power v/s Frequency, Histogram, Power density v/s Time can be obtained. These data are then used to plot vibration and SPP levels in frequency domain to develop the noise and vibration signature of that crown pinion for given cycles of operation. The tests on Bevel pinion and gear set were performed in the BEC, Bagalkot NVH lab facility. The gear set run successfully at double the rated torque for 30 million pinion cycles. And the signature of pinion failure was obtained. The results demonstrated the suitability of using the given bevel crown pinion and gears set for specified speed, high load application in differential gear box of an automobile.

On Gated Gaussian Impulsive Noise in M-QAM with Optimum Receivers

This paper presents an approach for the analysis of gated Gaussian impulsive noise and its effects in M-ary Quadrature Amplitude Modulation (M-QAM) schemes. In the approach, both amplitude variation and noisy pulse duration can be characterized as an amplitude modulation of the impulsive component by a discrete (binary or m-ary) random process. New exact expressions are obtained for the probability density function, autocorrelation function and power spectral density of the noise as well as for the bit error probability of M-QAM considering the maximum {\em a posteriori} probability optimum receiver. An important aspect of the proposed approach is the fact that the discrete random process incorporates the main parameters of the impulsive noise, such as amplitude, duration, instants in which the noise is added and time intervals between instants in which the noise is added.

ENVIRONMENTAL MODELING FOR TRAFFIC NOISE IN URBAN AREA

Traffic noise can be classified among the worst factors in terms of damage to people’s health and well-being. The trend of noise pollution modeling variable from the smart result of classic regressive models in the performance of many assessment models based on mathematical expressions, genetic algorithms and neural networks (of GRNN type, General Regression Neural Network). A methodological approach for the quantitative analysis of traffic noise in urban settings was proposed in the study. We present an analysis of the acoustic data measured in the city of Villa S. Giovanni (Italy), simultaneous measurement is of noise levels and vehicle flow and composition were done. Different prediction models were compared and a classification for the best assessment tool in the analysis of the equivalent level of noise Leq was given. The results show how the neural network approach provides better performance than the classical solution based on statistical analyses. The GRNN network is best suited to the simulation of the phenomenon seems and for the application in more complex areas, with greater variability in the traffic patterns, such as the case considered.

Systematic approach for wind noise analysis of buildings for engineering applications in Hong Kong

Wind noise for tall buildings can be a concern for densely populated area. It is needed to develop a systematic approach of wind noise analysis for building design in engineering applications. This paper presents an innovative approach based on a three-tier analysis framework for wind noise assessment of external features in urban environment. The framework is divided into screening review of external locations susceptible of impact; broad assessment of areas susceptible to impact; and focused model assessment. In Tier 1, review of facade design is conducted to identify susceptible impacted areas. Screening criteria related to wind speed, shapes, dimension of facade elements are derived for evaluation of facade/architectural forms. Fundamental principles are applied to different turbulent flows to estimate relative significance based on Lighthill's Theory of aerodynamic noise. Statistical analysis of meteorological data is conducted from weather, wind tunnel/AVA study data to form representative wind cond...

전달함수 기반의 선박 수중방사소음 해석 프레임워크 구현

The transfer function method is a widely used in the analysis of underwater radiated noise of ships because it is simple to implement and gives a simple way in the design stage requiring trade-off studies on various kinds of noise sources. In this study, a framework is implemented based on the transfer function method. The framework is interfaced to a software providing transfer functions of hull force to underwater radiated noise. The transfer function-based underwater radiated noise analysis approach is reviewed and the implemented framework structure is described. As an example, a numerical calculation of a virtual ship is carried out and its results are investigated in terms of applicability to real ship design project.

Chaos on Phase Noise of Van Der Pol Oscillator

Phase noise is the most important parameter in many oscillators. The proposed method in this paper is based on nonlinear stochastic differential equation for phase noise analysis approach. The influences of two different sources of noise in the Van Der Pol oscillator adopted this method are compared. The source of noise is a white noise process which is a genuinely stochastic process and the other is actually a deterministic system, which exhibits chaotic behavior in some regions. The behavior of the oscillator under different conditions is investigated numerically. It is shown that the phase noise of the oscillator is affected by a noise arising from chaos than a noise arising from the genuine stochastic process at the same noise intensity.

Impact of LER and Random Dopant Fluctuations on FinFET Matching Performance

Parameter variations pose an increasingly challenging threat to the CMOS technology scaling. Among the sources of variability, line-edge-roughness (LER) and random dopant (RD) fluctuations are significant in current technology nodes. In this paper, the impact of the LER and RD on the matching performance of FinFETs is investigated for the LSTP-32 nm node, where these devices represent an attractive alternative to the planar CMOS transistors. Line-edge-roughness contributions from the fin, top-, and side wall-gates of n- and p-channel FinFETs are compared by means of 2-D and 3-D technology computer-aided design (TCAD) simulations, performed with a quantum-corrected hydrodynamic model on large statistical ensembles. Correlations between geometrical roughness and resulting electrical parameters are analyzed to provide further insight into the impact of the LER. A noise analysis approach is adopted to evaluate the impact of RD fluctuations throughout the impurity concentration ranges of interest, providing a direct comparison with the line-edge-roughness contributions. The impact of the extension doping profile specifications on the LER- and RD-induced mismatch is investigated, highlighting the potential drawbacks of junction engineering.

Early probabilistic noise estimation for capacitively coupled interconnects

One of the critical challenges in today's high-performance IC design is to take noise into account as early as possible in the design cycle. Current noise analysis tools are effective at analyzing and identifying noise in the postroute design stage when detailed parasitic information is available. However, noise problems identified at this stage of the design cycle are very difficult to correct due to the limited flexibility in design and may cause additional iterations of routing and placement which adds costly delays in its time to market. In this paper, we introduce a probabilistic preroute noise analysis approach to identify postroute noise failures before the actual detailed route is completed. We introduce new methods to estimate the RC characteristics of victim and aggressor lines, their coupling capacitances, and the aggressor transition times before routing is performed. The approach is based on congestion information obtained from a global router. Since the exact location and relative position of wires in the design are not yet available, we propose a novel probabilistic method for capacitance extraction. We present results on two high-performance microprocessors in 0.18 /spl mu/m technology that demonstrate the effectiveness of the proposed approach.

A Noise Analysis Approach for Measuring the Decay Constants and the Relative Abundance of Delayed Neutrons in a Zero Power Critical Facility

This experimental work introduces a novice approach for the determination of the decay constants and the relative abundance of the delayed neutrons. The experimental procedure consists in obtaining the CPSD from the signals of two compensated ionization chambers in the frequency range from 0.005 to 5.0 Hz approximately. Assuming the point kinetic model, the theoretical expression for the CPSD can be written and the experimental CPSD can be fitted employing a least-square approach. The fitting parameters are ßi and λi. A preliminary experiment was made in the IPEN/MB-01 reactor. The least-square approach was able to fit all the betas for a six group model. However, it was not possible to fit the first decay constant (the group of longest half-live) accurately although the other five were achieved. The analysis reveals that the relative abundances of ENDF/B-IV and –VI are in a fair good agreement and that it is not only possible to perform successfully such measurements but also the decay constants and the relative abundance can be measured with a very good level of accuracy. ENDF/B-VI heavily underestimates the reactivity for small negative periods because its first decay constant is overestimated.

Analog circuit fault diagnosis based on noise measurement

In this paper, an analog circuit fault diagnosis method using a noise measurement and analysis approach is suggested. Compared to the conventional circuit fault diagnosis methods, this method can discover hidden and early circuit fault caused by the device defects. Since circuit fault diagnosis is more difficult than device-defect detection, in this paper the circuit output noise calculation, the comparison between the normal and failure conditions and the circuit fault diagnosis method have been discussed. Finally, an example of an active filter circuit fault diagnosis has been given by using this method.